Suicide before and during the COVID-19 Pandemic: A Systematic Review with Meta-Analysis

Synthesizing evidence to examine changes in suicide-related outcomes before and during the pandemic can inform suicide management during the COVID-19 crisis. We searched 13 databases as of December 2022 for studies reporting both the pre- and peri-pandemic prevalence of suicidal ideation, suicide attempts, or rate of death by suicide. A random-effects model was used to pool the ratio of peri- and pre-pandemic prevalence of suicidal ideation and attempt (Prevalence Ratio—PR) and rate of death by suicide (Rate Ratio; RR). We identified 51, 55, and 25 samples for suicidal ideation, attempt, and death by suicide. The prevalence of suicidal ideation increased significantly among non-clinical (PR = 1.142; 95% CI: 1.018–1.282; p = 0.024; k = 28) and clinical (PR = 1.134; 95% CI: 1.048–1.227; p = 0.002; k = 23) samples, and pooled estimates differed by population and study design. Suicide attempts were more prevalent during the pandemic among non-clinical (PR = 1.14; 95% CI: 1.053–1.233; p = 0.001; k = 30) and clinical (PR = 1.32; 95% CI: 1.17–1.489; p = 0.000; k = 25) participants. The pooled RR for death by suicide was 0.923 (95% CI: 0.84–1.01; p = 0.092; k = 25), indicating a nonsignificant downward trend. An upward trend of suicidal ideation and suicide attempts was observed during the COVID-19 pandemic, despite suicide rate remaining stable. Our findings suggest that timely prevention and intervention programs are highly needed for non-clinical adult population and clinical patients. Monitoring the real-time and long-run suicide risk as the pandemic evolves is warranted.


Introduction
Suicide constitutes a serious public health issue. Humans are usually vulnerable in the face of traumas such as wars and natural disasters, even choosing to end their own lives [1,2]. Several meta-analyses have examined suicide-related outcomes during infectious disease epidemics. The associations between epidemics and increased suicide risk are poorly supported [2][3][4], though a few review studies have reported higher suicide rates among older adults during SARS [4,5], more suicidal thoughts during an epidemic [2], and increased suicide attempts during SARS and Ebola [5]. It is unknown whether the COVID-19 pandemic and its consequences contribute to the rise of suicide risk. This study synthesized robust evidence to examine the potential changes in suicidal ideation, suicide attempt, and suicide before and during the COVID-19 pandemic.
The suicide risk was expected to be alarmingly severe over the short or long run following the outbreak of the COVID-19 pandemic, due to widespread and prolonged economic, social, health, and psychological vulnerability [6,7]. A few primary studies found an overall increase in the prevalence of suicidal ideation and attempts, and in the rate of death by suicide during the pandemic period compared with the pre-pandemic period [8][9][10], while other studies found a decreased trend [11][12][13], and some reported an overall stable trend [14][15][16]. Suicide studies during the pandemic tend to be methodologically poor [17], and high-quality evidence from an interrupted time-series study covering Inclusion criteria were that studies (a) reported the prevalence of at least one form of suicide-related outcome (i.e., suicidal ideation/thoughts, suicide attempt, and completed suicide), or sufficient information to compute these variables; (b) used a repeated cross-sectional (i.e., pseudo-longitudinal; multiple assessments on different samples), longitudinal (multiple assessments on the same sample), or retrospective design providing at least one set of data for pre-and peri-pandemic periods (as defined by the study); (c) included measurement of suicidal ideation/thoughts and attempts of participants and/or analyzed country-level or regional data for suicide death among the general population; (d) were peer-reviewed journal articles or preprints with full text available; and (e) were written in English or Chinese.
Exclusion criteria were that studies (a) were review articles, case reports, commentary, books, conference papers, or other documents that did not present empirical findings with detailed method illustrations; (b) had no sufficient data to calculate the effect sizes; and (c) were duplicate sources.

Selection Procedure and Data Extraction
All the searched articles retrieved from the databases were imported to EndNote 20 for reference management. After removing the duplicates, the remaining articles written in English were exported to ASReview version 0.18. (https://asreview.nl/; accessed on 8 December 2022), an open-source machine learning program, for efficient title and abstract screening [36], and Chinese articles were screened manually. We selected the default combination of naive Bayes, maximization, and TF-IDF (term frequency-inverse document frequency) as the active learning model, which can produce consistently good results across many datasets [36]. To train the active learning model, the authors pre-selected relevant and irrelevant articles from the imported literature set. The ASReview presented the article titles and abstracts in order of relevance, and the authors continued to judge the relevance of articles successively until 50 consecutive irrelevant articles were marked in a row [37]. Finally, two team members applied the inclusion and exclusion criteria to independently review the full texts of the remaining studies to identify the eligible ones. Any disagreements between the two reviewers were resolved by discussion with the PI.
The following information was extracted: (a) identification of the study (i.e., title, first author's name, publication year, country/region); (b) methodological characteristics (i.e., study design, sample size, definitions of pre-and peri-pandemic period, assessment approach for suicidal ideation and attempt/sources of death data,); (c) sample characteristics (i.e., population type, age and female proportion); and (d) outcome (i.e., prevalence/number of participants reporting suicidal ideation and/or suicide attempt for each period, or prevalence ratio comparing pre-and peri-pandemic assessment, rate/number of suicide death for both periods, or rate ratio comparing pre-and peri-pandemic data). Coding information varied slightly for studies reporting suicidal ideation, attempt, and death by suicide. In case of insufficient information on the published article, we contacted the authors via email. To consider financial factors, we retrieved data of gross domestic product/gross state product and unemployment rates [38][39][40][41] for both the pre-and peripandemic periods as defined by each included study, and calculated the ratio (peri/pre) to see how changes in financial factors would link to the variation in suicide rates. In addition, to monitor the impact of government reaction on suicide rate, we derived a resilience score (defined as an average score of reopening progress, COVID status, and quality of life in a country during the pandemic) from Bloomberg's Covid Resilience Ranking [42] for the latest data (29 June 2022), and COVID-19 government response indexes (i.e., stringency index, containment and health index, and economic support index) from the COVID-19 Government Response Tracker [43] for the latest data upon our analysis (9 December 2022). Two team members coded the included studies independently, and discrepancies were resolved through discussion with the PI.

Risk of Bias Assessment
The Joanna Briggs Institute (JBI) Critical Appraisal Instrument for prevalence studies was used to assess the risk of bias [35]. This instrument consists of nine items examining bias from a few factors (e.g., sample frame, sampling method, sample size, sample description, data analysis, measurement scale, and response rate). Each item can yield a score of 1 (the absence of bias) or 0 (the presence of bias). The total score ranged from 0 to 9, with a higher score indicating a lower risk of bias. Two members rated each study independently, and all disagreements between the two raters were resolved via discussion with the PI.

Statistical Analysis
Prevalence ratio (PR) or rate ratio (RR) represented the measure of effect size to examine the changes between the pre-and peri-pandemic periods in suicidal ideation, suicide attempt, and death by suicide. Specifically, prevalence ratios for suicidal ideation and attempt were calculated using event prevalence/count and sample size before and during the pandemic. For suicide death data, single estimate of the rate ratio with 95% CI for every included sample can be (a) directly extracted from publications or (b) calculated using rates of suicide death per 100,000 people in pre-and peri-pandemic periods [44]. To accommodate different types of input data, Comprehensive Meta-Analysis version 2.0 was used to conduct meta-analysis.
A random-effects model was used to pool PR or RR reported by each sample. We employed an index of Cochran's Q, Tau 2 , and I 2 statistics to test heterogeneity, with a p value of <0.05 for Q, Tau 2 , and I 2 > 50% indicating significant between-study heterogeneity [45]. Publication bias was determined through visual inspection of the asymmetry of the funnel plot and Egger's regression test [46]. Sensitivity analysis was conducted by omitting studies one by one (leave-one-out method) and excluding the studies with quality score ranked below 25% of the total before recalculating the pooled estimate, to determine the robustness of results [47].
Among our included samples, there were unneglectable heterogeneities regarding clinical and methodological characteristics. Some of the samples consisted of participants recruited from non-clinical settings (e.g., college or general population), and these were mainly prospective studies using self-report methods to measure suicidal outcomes, while the other samples were from clinical settings (e.g., emergency or psychiatric departments) whose suicide-related data were retrospectively extracted from medical diagnosis. Based on previous studies, the prevalence of suicidal ideation and suicide attempt can be different between individuals from non-clinical settings and clinical settings during both pre-and peri-pandemic periods [20,21,48,49]. Considering these differences in physical or mental health conditions, patterns of changes in suicide-related outcomes, and several methodological characteristics, the prevalence ratio for suicidal ideation and suicide attempts was analyzed by non-clinical and clinical samples. In general, the non-clinical sample refers to participants recruited from community and non-medical settings (e.g., college students and the general population), and the clinical sample refers to participants recruited from medical settings (e.g., patients from the emergency and psychiatric departments).
To determine the source of heterogeneity, we conducted subgroup analysis and metaregression. Specifically, we used a mixed effect model in subgroup analysis, where a random-effects model was used to pool samples within each subgroup, and a fixed effect model was used to pool the subgroup to yield the overall estimates. Meta-regression was run under the random-effects model to examine the effects of continuous variables on ratio. For studies reporting the pre-and peri-pandemic prevalence of suicidal ideation and/or attempt, population group (adolescent, younger group, general population/adult, or special group), study design (repeated cross-sectional, longitudinal, or retrospective), method (self-report or diagnosis) and timeframe (≤2 weeks or >2 weeks) for measuring suicidal outcomes, data collection (March-August 2020, September 2020-January 2021, or February 2021+), female percentage and risk of bias score were considered as potential moderators for effect sizes. Specifically, time for data collection was divided into 6-month intervals beginning from the onset of the pandemic to capture the changes in the global pandemic situation according to data from the World Health Organization [50]. In addition, we examined the impact of changes in GDP (Peri/Pre), unemployment rate (Peri/Pre), and several government-level COVID-19 indexes (i.e., resilience score, stringency index, containment and health index, economic support index) on the ratio of death by suicide.

Overview
There were 41 studies with 51 samples (28 non-clinical and 23 clinical samples, respectively) included for the analysis of suicidal ideation. Specifically, several studies contributed more than one sample due to multiple peri-pandemic data collection [9,54,59,62,64,106,108] or subsets of participants [103,111]. With an average risk-of-bias score of 7.2 (range = 5-9), the majority of included studies had adequate size and information for the sample, addressed response rate properly, and employed appropriate statistical methods. The most common limitations were deficiencies in the sample representativeness and recruiting methods, and unclear measurements (Table S2). Both non-clinical and clinical settings showed an increased prevalence of suicidal ideation during the pandemic compared with pre-pandemic periods, and significant heterogeneity was found within each setting (Table 3).

Non-Clinical Samples
The point estimates of suicidal ideation reported by 28 non-clinical samples ranged from 0.332 to 4.794, and the pooled prevalence ratio under the random effect model was 1.142 (95% CI: 1.018-1.282; p = 0.024), indicating a higher prevalence of suicidal ideation during the pandemic compared with the pre-pandemic period (Figure 2). The heterogeneity test results were significant (I 2 = 97.734%, tau 2 = 0.081, P Q < 0.05), indicating that there was a large difference in effect sizes between samples. Sensitivity analysis using leaveone-out method showed that most of the included samples did not affect the outcome substantially. However, when Ettman et al. [10] and Kasal et al. [9] were excluded separately, the respective pooled ratio (1.007-1.112) indicated a slight but non-significant increase in the peri-pandemic prevalence of suicidal ideation compared with pre-pandemic periods ( Figure S1). No publication bias was observed among the non-clinical samples according to the funnel plot ( Figure S2) and the non-significant results from Egger's tests (intercept = 2.61, t = 1.48, p = 0.151). The results of subgroup analysis are shown in Table 4; they suggest that the prevalence ratio varied by population type and study design. The highest PR was found among the general population (PR = 2.014, 95% CI: 1.604-2.529; p = 0.000), which indicated that suicidal ideation was twice as prevalent during the COVID-19 pandemic compared with before, while the prevalence of suicidal ideation in adolescents, younger (mostly college students) and special populations remained basically unchanged. After excluding the only one study [58] using retrospective design, the prevalence ratio was 1.318 (95% CI 1.132-1.535; p = 0.000) for repeated cross-sectional studies, suggesting the significantly increased prevalence of suicidal ideation during the pandemic relative to pre-pandemic times; meanwhile, longitudinal studies showed a non-significant decrease (PR = 0.842 95% CI: 0.666-1.063; p = 0.148). Meta-regression showed that neither female percentage nor quality score for non-clinical samples was associated with PR (Table S3). The results of subgroup analysis are shown in Table 4; they suggest that the prevalence ratio varied by population type and study design. The highest PR was found among the general population (PR = 2.014, 95% CI: 1.604-2.529; p = 0.000), which indicated that suicidal ideation was twice as prevalent during the COVID-19 pandemic compared with before, while the prevalence of suicidal ideation in adolescents, younger (mostly college students) and special populations remained basically unchanged. After excluding the only one study [58] using retrospective design, the prevalence ratio was 1.318 (95% CI: 1.132-1.535; p = 0.000) for repeated cross-sectional studies, suggesting the significantly increased prevalence of suicidal ideation during the pandemic relative to pre-pandemic times; meanwhile, longitudinal studies showed a non-significant decrease (PR = 0.842; 95% CI: 0.666-1.063; p = 0.148). Meta-regression showed that neither female percentage nor quality score for non-clinical samples was associated with PR (Table S3).  1 An aggregate of young people (aged 19-24 years old) and college students. 2 An aggregate of hotline callers and military veterans. 3

Clinical Samples
Of the 51 samples reporting suicidal ideation, 23 were conducted in a clinical setting. With a pooled estimate of 1.134 (95% CI: 1.048-1.227; p = 0.002), the prevalence ratio for each study ranged from 0.177 to 2.262 ( Figure 3). As indicated by the results, there was significant heterogeneity among the samples (I 2 = 71.029%, tau 2 = 0.018, P Q < 0.05). By excluding samples one by one or samples with lower quality [62,96,107], sensitivity analysis showed that none of the samples affected the outcome substantially ( Figures S3 and S4). Thus, despite variations across studies, the pooled estimate was robust enough to show an increasing trend of suicidal ideation among clinical patients during the pandemic. Through visual inspection of the funnel plot ( Figure S5) and the non-significant results in the Egger's tests (intercept = 0.096, t = 0.15, p = 0.882), the results showed that there was no publication bias among the clinical samples.  As all the clinical samples employed a retrospective design by extracting medical records, the subgroup analysis considered only population (adolescent vs. adult patients), method, and timeframe for measurement tool. According to Table 4, none of the above variables was a significant moderator for PR in the clinical samples. Nevertheless, metaregression (Table S3) showed that study quality was positively associated with the ratio, suggesting that higher-quality studies tended to report a larger increase in suicidal ideation (B = 0.08, p < 0.05).

Overview
There were 37 studies with 55 samples (30 non-clinical and 25 clinical samples, respectively) included for the analysis of suicidal ideation. Specifically, several studies contributed more than one sample due to multiple peri-pandemic data collection [9,65,70,75,106,108] or subsets of participants [75,103,111]. With an average risk of bias score of 7.5 (range = 4-9), the majority of included studies had adequate size and information for their sample, and they employed appropriate sampling and statistical methods. The most common limitations were deficiencies in sample representativeness and unclear criteria for judging suicide attempt (Table S2). Both non-clinical and clinical settings showed increased suicide attempts during the pandemic, compared with pre-pandemic periods, and the increase was higher among clinical participants. Significant heterogeneity was found in each setting (Table 5).  [16,59,60,62,63,92,[94][95][96]101,[103][104][105][106][107][109][110][111] conducted in the clinical setting (Prismatic colored as red refers to the pooled estimate).
As all the clinical samples employed a retrospective design by extracting medical records, the subgroup analysis considered only population (adolescent vs. adult patients), method, and timeframe for measurement tool. According to Table 4, none of the above variables was a significant moderator for PR in the clinical samples. Nevertheless, metaregression (Table S3) showed that study quality was positively associated with the ratio, suggesting that higher-quality studies tended to report a larger increase in suicidal ideation (B = 0.08, p < 0.05).

Overview
There were 37 studies with 55 samples (30 non-clinical and 25 clinical samples, respectively) included for the analysis of suicidal ideation. Specifically, several studies contributed more than one sample due to multiple peri-pandemic data collection [9,65,70,75,106,108] or subsets of participants [75,103,111]. With an average risk of bias score of 7.5 (range = 4-9), the majority of included studies had adequate size and information for their sample, and they employed appropriate sampling and statistical methods. The most common limitations were deficiencies in sample representativeness and unclear criteria for judging suicide attempt (Table S2). Both non-clinical and clinical settings showed increased suicide attempts during the pandemic, compared with pre-pandemic periods, and the increase was higher among clinical participants. Significant heterogeneity was found in each setting (Table 5).

Non-Clinical Samples
The prevalence ratio of suicide attempt reported by 30 non-clinical samples ranged from 0.333 to 6.261, and the pooled prevalence ratio under the random effect model was 1.14 (95% CI: 1.053-1.233; p = 0.001), indicating that suicide attempts were more prevalent during the COVID-19 pandemic than during pre-pandemic periods (Figure 4). Though effect sizes were substantially heterogenous among the samples (I 2 = 99.996%, tau 2 = 0.036, P Q < 0.05), a sensitivity analysis using the leave-one-out method or by excluding lower quality studies [66] showed that the increased trend of suicide attempts was robust (Figures S6 and S7). Through visual inspection of the funnel plot ( Figure S8) and the non-significant results of the Egger's tests (intercept = 6.52, t = 0.17, p = 0.865), no publication bias among the non-clinical samples was observed.
clinical settings.
The results of the subgroup analysis are shown in Table 6. Excluding only one prisoner sample, the general population (PR = 1.218, 95% CI: 1.089-1.362; p = 0.001) showed the largest increase in suicide attempts compared with adolescent and younger samples, despite the fact that the differences were insignificant. Meta-regression showed that neither the female percentage nor the quality score for the non-clinical samples were associated with PR (Table S4).  [9,12,15,66,68,72,74,75,93,[97][98][99][100]102,108,112,113] conducted in the non-clinical setting (Prismatic colored as red refers to the pooled estimate).
The results of the subgroup analysis are shown in Table 6. Excluding only one prisoner sample, the general population (PR = 1.218, 95% CI: 1.089-1.362; p = 0.001) showed the largest increase in suicide attempts compared with adolescent and younger samples, despite the fact that the differences were insignificant. Meta-regression showed that neither the female percentage nor the quality score for the non-clinical samples were associated with PR (Table S4).

Clinical Samples
Of the 55 samples reporting suicide attempt, 25 were conducted in a clinical setting. With a pooled estimate of 1.32 (95% CI: 1.17-1.489; p = 0.000), the prevalence ratio for each study ranged from 0.71 to 2.379 ( Figure 5), and the effect size was heterogenous (I 2 = 70.021%, tau 2 = 0.052, P Q < 0.05). The increased trend for suicide attempt during the pandemic was robust, as pooled estimates did not change substantially based on the results (Figures S9 and S10) of the leave-one-out sensitivity analysis and the analysis excluding lower quality studies [96,107]. Visual inspection of the funnel plot ( Figure S11) and the non-significant results in the Egger's tests (intercept = −0.63, t = 0.86, p = 0.397) indicated an absence of asymmetry in the funnel plot. These results showed no publication bias among the clinical studies reporting suicide attempt. All clinical samples (k = 25) employed a retrospective design by extracting medical records; subgroup analysis considered only population (adolescent or adult patients), method and timeframe for measurement tool, and time for data collection. According to subgroup analysis (Table 6) and meta-regression (Table S4), no significant moderators were found for PR of suicide attempts in the clinical samples.

Meta-Analysis for Death by Suicide
A total of 25 samples were reported by 20 studies, as some studies included genderspecific [81] or multiple peri-pandemic [84,89,114] data. The risk-of-bias score for the included samples ranged from 5 to 9 (average = 7.8), and 75% of the samples scored above 7. All samples were nationally or regionally representative, while some of them did not provide detailed demographics, criteria for judging, or source of suicide death (Table S2).
All clinical samples (k = 25) employed a retrospective design by extracting medical records; subgroup analysis considered only population (adolescent or adult patients), method and timeframe for measurement tool, and time for data collection. According to subgroup analysis (Table 6) and meta-regression (Table S4), no significant moderators were found for PR of suicide attempts in the clinical samples.

Meta-Analysis for Death by Suicide
A total of 25 samples were reported by 20 studies, as some studies included genderspecific [81] or multiple peri-pandemic [84,89,114] data. The risk-of-bias score for the included samples ranged from 5 to 9 (average = 7.8), and 75% of the samples scored above 7. All samples were nationally or regionally representative, while some of them did not provide detailed demographics, criteria for judging, or source of suicide death (Table S2).
Meta-regression was conducted to test whether counties' resilience and governmentlevel economic and societal indexes during the pandemic would contribute to the between-study heterogeneity on death by suicide. However, the moderating effects for these indexes were not significant (Table S5). The subgroup analysis showed that the trends for suicide death were significantly different between national and regional samples (p = 0.01). Despite the country-level rate of death by suicide remaining stable (RR = 0.99, 95% CI: 0.91-1.1; p > 0.05), data from regional samples reported a decreased trend (RR = 0.82, 95% CI: 0.73-0.92; p = 0.001).

Discussion
To our knowledge, this work was the first meta-analysis that assessed the changes in the prevalence of suicidal ideation, suicide attempt, and rate of death by suicide before and during the COVID-19 pandemic across populations, using intertemporal data from repeated cross-sectional retrospective, longitudinal, and retrospective studies. We included 45 studies with 67 samples, and most of the included studies had a low risk of coverage bias, sample size estimation, and statistical analysis. Compared with the prepandemic period, the prevalence of suicidal ideation and suicide attempt increased significantly during the COVID-19 pandemic among both non-clinical and clinical samples, while the rate of death by suicide remained mostly unchanged in the synthesis of the existing evidence.
Meta-regression was conducted to test whether counties' resilience and governmentlevel economic and societal indexes during the pandemic would contribute to the betweenstudy heterogeneity on death by suicide. However, the moderating effects for these indexes were not significant (Table S5). The subgroup analysis showed that the trends for suicide death were significantly different between national and regional samples (p = 0.01). Despite the country-level rate of death by suicide remaining stable (RR = 0.99, 95% CI: 0.91-1.1; p > 0.05), data from regional samples reported a decreased trend (RR = 0.82, 95% CI: 0.73-0.92; p = 0.001).

Discussion
To our knowledge, this work was the first meta-analysis that assessed the changes in the prevalence of suicidal ideation, suicide attempt, and rate of death by suicide before and during the COVID-19 pandemic across populations, using intertemporal data from repeated cross-sectional retrospective, longitudinal, and retrospective studies. We included 45 studies with 67 samples, and most of the included studies had a low risk of coverage bias, sample size estimation, and statistical analysis. Compared with the pre-pandemic period, the prevalence of suicidal ideation and suicide attempt increased significantly during the COVID-19 pandemic among both non-clinical and clinical samples, while the rate of death by suicide remained mostly unchanged in the synthesis of the existing evidence.
Our findings showed an upward trend of suicidal ideation and suicide attempt during the COVID-19 pandemic among both non-clinical and clinical samples. These results were consistent with a few studies during the pandemic, which warned about the increased risks of suicidal thoughts and behaviors relative to pre-pandemic periods among the general population and inpatients [22][23][24]. The outbreak of the COVID-19 pandemic had brought profound health, psychological, social, and economic consequences worldwide, which might have heightened various suicide risk factors [6,7]. As found by a meta-analysis looking at data spanning 50 years [115], hopelessness, mental health issues (e.g., depression and anxiety), socioeconomic status, and stressful life events were among the top predictors for suicide-related outcomes. These factors were also applied to the pandemic context [24]. During the pandemic, with lockdown measures implemented, individuals experienced overwhelming fears and worries about COVID-19 due to health issues, uncertainties about the future, stigmatization, and misinformation from media, which were associated with higher hopelessness under the pandemic context [116]. Additionally, the COVID-19 pandemic had been described as a tsunami, leading to mental disorders worldwide [117], and a wide range of studies had suggested the severe psychological impacts of increased distress, depression, anxiety, insomnia, and loneliness brought by the pandemic across populations [118][119][120][121]. These psychological symptoms might be long-lasting, increasing the risk for suicidality [7]. People also suffered from financial strain, unemployment, and economic uncertainty due to the global economic downturns, which constituted societal risk factors for developing suicidal ideation and attempts during the pandemic [122]. Recent studies have also reported the rise of other risk factors for suicide, such as weakened social support, poor health, increased interpersonal conflict, domestic violence, and alcohol consumption [6,[123][124][125][126]. The wide-ranging adverse effects of the pandemic may have put individuals at a disadvantage and triggered the increased suicide-related outcomes.
Notably, the adult general population showed a larger increase in both suicidal ideation and suicide attempt, and the increase in suicidal ideation was particularly noticeable. The PR for suicidal ideation was 2.014 (95% CI: 1.604-2.529; p = 0.000), indicating a doubled prevalence of suicidal ideations during the pandemic, with a slight increase in suicide attempt (PR = 1.218; 95% CI: 1.089-1.362; p = 0.001). The adult general population in our study was aged above 25 and mostly in their 30s-50s. Middle-aged adults are usually the pillar of a family, with heavier financial and caregiving responsibilities. Thus, economic adversities and lockdown measures can threaten this population, making them more vulnerable to suicide [127]. In addition, the larger increase in ideation than attempt echoes the pyramid theory of suicidal trajectories [128]. According to the theory, suicide-related outcomes develop in an ascending flow from suicidal ideation at the bottom of the pyramid, moving up to plan and attempt, and ultimately reaching the peak of the pyramid, completed suicide. Individuals can stop at any stage once they have started the "suicidal career", but most people only have suicidal thoughts, with few actually taking action [129]. The gap between these stages can be understood by the interpersonal theory of suicide, which suggests that despite a strong suicidal desire, the step toward attempt requires one's ability (e.g., fearlessness and pain insensitivity) to act on the thoughts [130]. Thus, not everyone who develops suicidal ideation engages in suicidal behaviors, which can account for the differences in incremental movement from suicidal ideation to attempt during the pandemic among the non-clinical adult samples.
Interestingly, our clinical samples showed more increases in the prevalence of suicide attempt than suicidal ideation. These findings do not contradict the pyramid theory. Previous studies found that suicidal thoughts were often under-documented in clinical settings [131], and those who attempted suicide were more prone to present in emergency and psychiatric departments compared to those only with suicidal ideation. In addition, referral to health services was further hindered by the lockdown measures during the pandemic, resulting in a larger proportion of community individuals with only suicidal thoughts being underdiagnosed [132,133]. These reasons can also explain our results that suicidal ideation among non-clinical adults increased more than the clinical samples, which is congruent with a previous finding [20].
The results for suicidal ideation and attempt were mostly robust, based on the sensitivity analysis. The only exception was found by excluding several non-clinical samples one by one [9,10], the pooled estimates which changed substantially, and the fact that the increases in suicidal ideation became smaller and nonsignificant, indicating the peculiarly large in-creases in these studies. Both studies employed a repeated cross-sectional design; therefore, those who responded to the survey in two periods may have differed in characteristics. Though both studies collected data from nationwide adult samples during the pre-and peri-pandemic periods, participants recruited during the pandemic were experiencing more adverse conditions for suicidality, as mentioned above (e.g., mental disorders, economic disadvantage). This finding again suggests that suicide risk factors were magnified by the pandemic, and the adult population may have suffered more. In any case, our subgroup analysis among non-clinical samples showed that, compared with the longitudinal study, suicidal ideation reported by repeated cross-sectional studies increased more. Therefore, it is possible that stressors may have affected survey participation [10], as psychologically vulnerable individuals may pay more attention to mental health information during the pandemic due to attentional bias.
Suicide death did not change significantly in terms of the pooled RR during the pandemic, compared with the pre-pandemic period. This trend agrees with previous findings from 33 countries and individual groups [18,20]. However, the trend was different at the regional and country level, with a significant downward trend shown by using regional data (RR = 0.82, 95% CI: 0.73-0.92; p = 0.001). The difference was also found in the state of Connecticut, showing a lower suicide rate compared with the national level [82]. The possible explanation might be the small sample size or the larger coverage of a single race included by regional data, which is not representative of the national profile. This implies the need to consider regional differences and the representativeness of the samples when interpreting the suicide rate.
Our findings have significant implications for future suicide management. Although the overall rate of death by suicide did not increase, suicide concerns are still serious, as this study showed that suicidal ideation and suicide attempts have been more prevalent since the pandemic. Having suicidal desires and acting on the thoughts are the prior stages of final death by suicide; such suicidal processes can be unstable and vary in duration. For example, the average duration for females and males before displaying explicit suicidal acts was 52 and 31 months [129]. In other words, a "suicidal career" takes time to progress to the final stage, though this only applies to a small proportion of suicidal individuals [134]. Thus, the alarming increases in suicidal ideation and suicide attempts during the pandemic point to the need for prompt suicide screening and prevention-especially among the members of the general public who might be underdiagnosed-and specifically, timely interventions targeting suicidal individuals to halt their exacerbation.
This study has a few limitations. First, some included studies did not provide sufficient information (e.g., gender distributions and timeframe for measurement) to be coded for the moderation analysis, making our subgroup analysis and meta-regression results less convincing. Second, there may have been an overlap in the subgroup of the adult general population and younger group (mostly college students), as the studies targeting the general population usually included people above 18, despite the larger proportion being middle-aged. Third, considerable heterogeneity still exists in all outcomes, even after considering potential moderators, and none of the investigated factors can account for the variability among effect sizes for death by suicide, which was similar to the previous findings [18]. Future studies are recommended to examine other potential sources of heterogeneity. Finally, the included samples only covered data up to November 2021, most of which were conducted in 2020. Such a delay may have compromised the validity of our findings, as suicidality and its risk factors are fluid in nature and vary within short periods, according to the fluid vulnerability theory of suicide [135]. As the pandemic evolves, the present suicide situation might be changing, so it is necessary to have ongoing monitoring and real-time surveillance.

Conclusions
In conclusion, our study provides an overview of the changes in the prevalence of suicidal ideation and suicide attempts across populations and the national or regional rate of death by suicide since the outbreak of the COVID-19 pandemic. Although the overall rate of death by suicide remained basically unchanged during the pandemic, suicidal ideation and suicide attempt were more prevalent compared with the pre-pandemic period, especially among the adult general population and clinical patients. Considering the heightened suicide risk factors, such as mental health problems and economic vulnerability during the pandemic, large-scale suicide screening for the public and timely intervention programs for high-risk groups are highly needed. The continuously changing pandemic underscores the importance of ongoing monitoring and surveillance for suicidality.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/ijerph20043346/s1, Figure S1. Sensitivity analysis for non-clinical samples reporting suicidal ideation (leave-one-out method); Figure S2. Funnel plot for non-clinical samples reporting suicidal ideation; Figure S3. Sensitivity analysis for clinical samples reporting suicidal ideation (leave-one-out method); Figure S4. Sensitivity analysis for clinical samples reporting suicidal ideation (exclude lower-quality samples); Figure S5. Funnel plot for clinical samples reporting suicidal ideation; Figure S6. Sensitivity analysis for non-clinical samples reporting suicide attempt (leave-one-out method); Figure S7. Sensitivity analysis for non-clinical samples reporting suicide attempt (exclude lower-quality samples); Figure S8. Funnel plot for non-clinical samples reporting suicide attempt; Figure S9. Sensitivity analysis for clinical samples reporting suicide attempt (leaveone-out method); Figure S10. Sensitivity analysis for clinical samples reporting suicide attempt (exclude lower-quality samples); Figure S11. Funnel plot for clinical samples reporting suicide attempt; Figure S12. Sensitivity analysis for samples reporting suicide death (leave-one-out method); Figure S13. Sensitivity analysis for samples reporting suicide death (exclude lower-quality samples); Figure S14. Funnel plot for samples reporting suicide death; Table S1. PRISMA checklist; Table S2. Risk of bias assessment; Table S3. Summary of meta-regression for non-clinical and clinical samples reporting suicidal ideation; Table S4. Summary of meta-regression for non-clinical and clinical samples reporting suicide attempt; Table S5. Summary of meta-regression for samples reporting death by suicide; File S1. Full search strategy.

Data Availability Statement:
The data that support the findings of this study are available from the corresponding author, N.X.Y., upon reasonable request.